post-training-quantization
There are 45 repositories under post-training-quantization topic.
intel/neural-compressor
SOTA low-bit LLM quantization (INT8/FP8/INT4/FP4/NF4) & sparsity; leading model compression techniques on TensorFlow, PyTorch, and ONNX Runtime
666DZY666/micronet
micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、Low-Bit(≤2b)/Ternary and Binary(TWN/BNN/XNOR-Net); post-training-quantization(PTQ), 8-bit(tensorrt); 2、 pruning: normal、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization fuse for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape
alibaba/TinyNeuralNetwork
TinyNeuralNetwork is an efficient and easy-to-use deep learning model compression framework.
SqueezeAILab/SqueezeLLM
[ICML 2024] SqueezeLLM: Dense-and-Sparse Quantization
ModelTC/llmc
[EMNLP 2024 Industry Track] This is the official PyTorch implementation of "LLMC: Benchmarking Large Language Model Quantization with a Versatile Compression Toolkit".
Xiuyu-Li/q-diffusion
[ICCV 2023] Q-Diffusion: Quantizing Diffusion Models.
megvii-research/FQ-ViT
[IJCAI 2022] FQ-ViT: Post-Training Quantization for Fully Quantized Vision Transformer
megvii-research/Sparsebit
A model compression and acceleration toolbox based on pytorch.
sayakpaul/Adventures-in-TensorFlow-Lite
This repository contains notebooks that show the usage of TensorFlow Lite for quantizing deep neural networks.
Hsu1023/DuQuant
[NeurIPS 2024 Oral🔥] DuQuant: Distributing Outliers via Dual Transformation Makes Stronger Quantized LLMs.
ModelTC/TFMQ-DM
[CVPR 2024 Highlight & TPAMI 2025] This is the official PyTorch implementation of "TFMQ-DM: Temporal Feature Maintenance Quantization for Diffusion Models".
hkproj/quantization-notes
Notes on quantization in neural networks
ModelTC/QLLM
[ICLR 2024] This is the official PyTorch implementation of "QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Models"
Sanjana7395/static_quantization
Post-training static quantization using ResNet18 architecture
zysxmu/FDDA
Pytorch implementation of our paper accepted by ECCV 2022-- Fine-grained Data Distribution Alignment for Post-Training Quantization
shieldforever/NeuronQuant
[ASP-DAC 2025] "NeuronQuant: Accurate and Efficient Post-Training Quantization for Spiking Neural Networks" Official Implementation
iszry/DI2N-PTQ4DM
Improved the performance of 8-bit PTQ4DM expecially on FID.
GongCheng1919/bias-compensation
[CAAI AIR'24] Minimize Quantization Output Error with Bias Compensation
Rumeysakeskin/ASR-Quantization
Post-training quantization on Nvidia Nemo ASR model
yester31/Quantization_EX
quantization example for pqt & qat
motokimura/pytorch_quantization_fx
An example to quantize MobileNetV2 trained on CIFAR-10 dataset with PyTorch FX graph mode quantization
likholat/openvino_quantization
This sample shows how to convert TensorFlow model to OpenVINO IR model and how to quantize OpenVINO model.
smpanaro/norm-tweaking
Post post-training-quantization (PTQ) method for improving LLMs. Unofficial implementation of https://arxiv.org/abs/2309.02784
satya15july/quantization
Model Quantization with Pytorch, Tensorflow & Larq
ssi-research/eptq
Implementation of EPTQ - an Enhanced Post-Training Quantization algorithm for DNN compression
yester31/TensorRT_ONNX
Generating tensorrt model using onnx
yester31/TensorRT_Examples
TensorRT in Practice: Model Conversion, Extension, and Advanced Inference Optimization
yugwangyeol/PTQ-QAT-Image-Classification
[Project] Edge computing PTQ/QAT Comparison Experiment
AndreiZoltan/ptq_resnet20
Low-bit (2/4/8/16) Post Training Quantization for ResNet20
Gaurav-Van/Fine-Tuning-LLMs
Introductory Guide where we will talk about Different Techniques of Fine Tuning LLMs
generalMG/Medical-Dataset-Deep-Learning-Quantization-Data-Analysis
The repository discusses a research work published on MDPI Sensors and provides details about the project.
TanyaChutani/Quantization_Tensorflow
Quantization for Object Detection in Tensorflow 2.x
yashmaniya0/Quantization-of-Image-Classification-Models
Comprehensive study on the quantization of various CNN models, employing techniques such as Post-Training Quantization and Quantization Aware Training (QAT).
Inpyo-Hong/Model-Compression-Paper-List
Model Compression Paper List (Focusing on Quantization, Particularly Zero-Shot Quantization)
OmidGhadami95/EfficientNetV2_Quantization_CK
EfficientNetV2 (Efficientnetv2-b2) and quantization int8 and fp32 (QAT and PTQ) on CK+ dataset . fine-tuning, augmentation, solving imbalanced dataset, etc.